Notes on the Demand for Health Care and Cost-Sharing

Demand

Someone's subjective idea
(may be based on a formula applied objectively, but the choice to use
the formula was someone's subjective idea.
Money is not a factor.

Objectively observable as behavior in the market.
Money is a key factor. "Demand" is also called "effective demand,"
because it's expressed only by spending money.

Example of "need": Hill-Burton hospital-building-subsidy program
used 4.5 bed/1000 pop formula (more in rural areas). On the other
hand, DHEC's "need" formula for hospital beds is based on historical ratios
of utilization to population. This makes it a demand measure.

Health plans that focus on need and ignore demand will face under- or
over-utilization of service capacity. If one believes quantity demanded
is too little (e.g. indigents) or too much (e.g. overuse of emergency room)
relative to need, then quantity demanded must be manipulated,
by changing price or other costs to buyer, or
by changing demand through marketing or de-marketing.

Demand is a relationship between price and quantity. We can study
how high the demand is -- the position of the demand curve
-- and
how elastic (responsive to price changes) demand is --
the steepness and shape of the curve.

Elasticity

This concept is used in some of the articles which follow. There
are two interactive lectures about this. Here are some details on
the concept.

Elasticity of demand is a measure of the responsiveness of the
demanded quantity to price changes.

The elasticity of demand for something is:
For instance, If price goes up 1% and as a result sales fall 2%, the
elasticity is -2%/1%=-2.
Elasticity, as a measure of responsiveness to price change, is an alternative
to the slope, which would be
Example of calculation (from Phil Jacobs' book):

I used 1175 and $3.125 in the elasticity formula. These are averages
of the before and after quantity and price levels. 1175 = (1150+1200)/2.
$3.125 = ($3.00 + $3.25)/2. The elasticity calculated this way is
called the arc elasticity.

Notice how the slope has units (tests per dollar), but the elasticity
does not. The elasticity has no units because the numerator is tests/tests
and the denominator is $/$. All the units cancel out, leaving a unitless
number. This means you get the same answer regardless of what units
you use. This lets you compare elasticities of totally different
products, like medical care, petroleum, and videocassette rentals.

One interpretation of elasticity of demand:
It's the percentage change in quantity demanded that comes from a 1%
change in the price.

Here's another way to interpret elasticity of demand:
Suppose you raise the price of something you're selling.
Will you make more money? The answer depends on the elasticity of
demand.

Elasticity (absolute value, ignoring the minus sign)

If price goes up,

Demand is categorized as:

> 1

spending goes down.

Elastic

= 1

spending stays the same.

Unitary elasticity

< 1

spending goes up.

Inelastic

What are examples of products or services whose demand is elastic?
Inelastic?

Hot tip: If you want to impress economists, say: "That
depends on the elasticity, doesn't it?"

The small elasticities observed for medical care demand imply that higher
med care prices will cause people to cut back some, but they will not much,
so the total amount spent on care will go up.

Elasticity can be used for other things besides quantities and prices.
The elasticity of health status with respect to medical care expenditure
is the percentage difference in health status divided by the percentage
difference in medical care expenditure. The cause (e.g. expenditure
change) is in the denominator. The effect (health status change)
is in the numerator.

The advantage of elasticity over slope is that, as mentined, elasticities
are numbers with no units.
A disadvantage of elasticity is the other side of its advantage:
The unitless number obscures the problems with measuring the quantities
in the equation, such as health status.

The Position of the Medical Care Demand Curve

What determines how high demand is (i.e. how much medical care will
be bought at various prices):

Physical condition
Social factors

affect need for care as perceived by individual and society

Income
Insurance

affects how much the person can pay

Physical and cultural/demographic factors can vary regionally or even
locally.

Regarding income: The usual finding is that medical spending goes
up as income goes up, but less than proportionally. In other words, the
income elasticity of med care demand is between 0 and 1.

Insurance and the Demand for Health Care

Insurance plays a major role in shaping health care, unlike most goods
and services. If we define insurance broadly, there are three kinds
of insurance:

Voluntary insurance purchase -- many of us buy insurance to assure us access
to services that we could not afford to pay for directly.

Rule of rescue -- we don't like to see people suffer or die needlessly.
We expect providers to give service to people in immediate need even if
they don't pay.

Government insurance extends the rule of rescue to general health care
for the elderly and some of the poor.

(Irony about rule-of-rescue emergency care: Prices charged do affect
incentive to seek care among people who can afford to pay. And you
can pay to get priority: In a discretionary situation, choosing to
go by ambulance gets you to the front of the line.)

Demand, Need, and Copayments

How big is moral hazard in health insurance? How much does health
insurance induce people to buy health care that they don't much need?
The RAND health insurance study sought to answer these questions (which
are not the same, by the way).

This article is a major one in a series coming out of the $70 million
government-funded RAND health insurance study. In this portion of
the study, 3958 adults were followed over 8 years. 14 insurance plan
incentive schemes tried, from no incentive -- free care -- through various
copayments of 25 to 50%, to catastrophic insurance that required 95% payment
for all services until the family had spent 15% of its income or $1000,
whichever was less. (I imagine they used 95% rather than 100% to
give the families an incentive to send in their medical bills.)

The free-care vs. copayment comparison allows you to trace out a demand
curve

Adults who had to pay used about 2/3 of the ambulatory visits and hospitalizations
of those who didn't. An earlier article (Newhouse et al, NEJM 305(25) Dec. 17, 1981, 1501-7)
reported this. There was little or no significant difference among the pay plans. As far as they could tell, 25% copayment had the same effect as 95%. Low income families responded more to copayments than higher income families, but not by much in most years and locations. The authors point out that low income families will illnesses would exceed their deductible sooner than higher income families, because the deductible was proportional to income.

This article goes beyond demand to need, by exploring the impact of
differences in utilization on health status.

For the whole population, differences in health status are found only
for persons with poor vision or high blood pressure.

The impact of cost sharing is clearest in lowest income group (bottom
20%).

Not clear if cost sharing has impact in the rest of the population.

One conclusion is that specifically targeted programs (vision, hypertension,
especially for poor) are more cost-effective than free care for all at
improving public health status. (Cost effective means more bang for
the buck.)

A note about the cash payment to those with catastrophic insurance:
People who had the 95% copayment plan got a cash payment of about $80 a
month. This meant that they had cash that they could spend on health
care, if they chose, but they could chose to spend it on something else
instead. Orthodox economists believe that it's better to give people
money than services of the same value. That way people can spend
the money in a way that maximizes their satisfaction. If they want
medical service, they can buy it, but if they want something else more,
they can buy that. Put another way, the investigators suspected that
many people would rather forgo seeking medical care for some minor (to
them) conditions and spend the money saved on something else. If
care is free, a person may go to the emergency room and spend $100 worth
of society's resources on treatment of a headache, say. If the person
has to pay part or all of that $100, he/she may prefer to take an aspirin
at home and spend the other $99.95 on something else. Either way
uses up $100 worth of society's resources, but the second way gives the
person with the headache more satisfaction.

In the same issue was an editorial comment, Relman, A. S., "The Rand
Insurance Study, Is Cost Sharing Dangerous to Your Health?" New Engl J
Med, December 8, 1983, 309, 1453. This is not in the packet.

Relman notes that the population studied was mostly health adults under
age 65. Limited measures of health status were reported. The
study does show the difficulty and expense of experiments to determine
how health care relates to health status.

My comment: The worst (highest copayment) plan in the experiment
is better than what the poor usually have. It's better than Medicaid
for hospitalizations, and certainly better being medically indigent and
having to rely on whatever care the public hospitals are willing to provide
free.

Cholestyramine can reduce the risk of heart disease, but daily therapy
costs $1861.50 per year for the drug alone.
Cholestyramine
$9,300,000 average cost per life saved
$780,000 per coronary heart disease
death or non-fatal MI (heart attack) averted.
Free health care for all men over 50 saves lives at an average cost
of
$654,000 (compared with 95% copayment),
or
$378,000 (compared with 50% copayment).
Free care for everyone saves lives at average cost of
$726,700.
The 4th stool guaiac test detects colon cancers at an average cost
of
$906,088 in 1984 dollars. ($1
million in 1987 $)

Even controlling for type of insurance coverage, persons in the lower
1/3 of the income distribution used the ER 64% more than persons in the
upper 1/3. Maybe the poor were accustomed to ER use. Maybe
there was a lack of private docs in the poor areas.

Shapiro et al re-analyzed some of the Rand data, looking at different
responses among patients with more serious vs. less serious symptoms.
For those with minor symptoms, cost sharing meant 1/3 less visits as above.
For serious symptoms, cost sharing doesn't affect propensity to seek care,
except for poor. Here "poor" means the low 40% of socioeconomic status
(Brook used 20%).

Health status measured by presence of various symptoms in annual survey.
Survey asked about health status during previous month.

Among those who were sick when the HIE (health insurance experiment)
began, the poor reported more symptoms than the non-poor.
The poor in the free care plan improved to where they were no sicker
(serious symptoms) than the non-poor.
The poor in the copayment plans also improved some, but remained sicker
(serious symptoms) than the non-poor.

Why the improvement in both groups?
They say: Regression towards the mean. Whenever you divide
people into a sick group and a well group, some people in the sick group
will get better on their own. Meanwhile, some people in the well
group will get sick.
I might add, as mentioned above: Even the catastrophic plan was
better than what many of the poor had before. They now had cash to spend,
and they had insurance against big expenses.

Manning

This is not in the packet, but has some amusing ideas if you're interested
to read it:
Manning, W.G., et al, "Health Insurance and the Demand for Medical
Care," American Economic Review, June 1987, 77:251-277.

Lots of economeze. Read the understandable parts and skip
the rest.

Manning's Points:
Demand. Summarizing the results of the Brook and O'Grady articles,
medical care demand elasticity is generally about -0.2.

Manning says insurance causes a welfare loss of $37-$60 billion / year
(1984 $). Here's the idea: When goods or services are free
(or subsidized), we buy more of them than we would if we have to pay.
We might spend $50 worth of resources on a service that's worth only, say
$5, to us. Manning et al would call that a welfare loss of $45, because
somebody else would presumably have been willing to pay $50 for those resources
(that's why we say they are worth $50). Add that up over all free
or heavily subsidized medical care and you get $37-$60 billion, or about
$160 per person per year in the U.S. (You estimate total welfare
loss from the amount spent on medical care and from your estimated elasticity
of demand.)

Was the experiment the money spent on it?
Manning gives the experiment credit for reforms in health insurance
that have been sweeping the U.S. since its results were announced, particularly
insurers imposing new "first dollar charges" -- deductibles and coinsurance.
The experiment cost $136 million in 1984 present value. That's
only 1.5 days worth of welfare loss, and is only 1 week's worth of the
$7 billion annual savings Manning et al attribute to the imposition of
first dollar charges so far. So the experiment was well worth it,
he says.

Moving up the 1990's, this study took advantage of Medicare starting
to pay for mammograms for screening for breast cancer. (Medicare already
paid for diagnostic mammograms for women whose examination found a lump.)
The effect of copayments are documented. Note, though, that this study
could not randomly assign patients to insurance groups, as RAND could

Economic factors affect even those on Medicare. OK, you're not
surprised.

Article looks at demand and need for mammograms. Women in this
age group assumed to need a mammogram every two years. Study
was of Medicare bills during the first two years in which Medicare paid
for mammography. This payment, like all Medicare, is subject to the
Medicare deductible, then $100 per year. After deductible, patient
could pay up to about $20 in copayment and "balance billing." Supplemental
insurance would take care of all or most of this, to varying degrees.

14% of women without supplemental insurance had a mammogram in the two-year
period.
24% of women with Medicaid paying their share had a mammogram.
40% of women with self-paid supplemental insurance had a mammogram
45% of women with employer-paid supplemental insurance had a mammogram

The problem with making a judgement from these statistics alone is confounding
factors. General economic circumstances and attitudes affect this
decision, and also affect the likelihood of having supplemental insurance.
For example, people with good jobs (4th category above) have more income.

"Multivariate" analysis attempts to separate the causes and isolate
the effect of insurance given the other factors, like age, race, income,
education, self-image, ... [More on this next semester in 716.] Leads
to "adjusted odds ratios" in table 4 (p. 1141), which actually aren't that
different from the raw numbers. For instance, the adjusted odds ratio
of 3 for employer-paid insurance means women with that insurance are three
times as likely as women without supplemental insurance to have had a mammagram.
45% is about 3 times 14%.

A problem with studies of this type is self-selection. People
who expect or intend to use more services are more likely to buy insurance.
The apparent effect of insurance on demand is actually a result of the
prior disposition. This would be most true of women who pay for their
own supplemental insurance. It would be less true of those on Medicaid
and those with employer-paid insurance.

As a general point in marketing (or health promotion and education),
there was still plenty of work to be done in encouraging demand, even among
those with insurance. Half of them didn't get a mammogram.
Still, price is clearly a factor.

Reviewing twenty years of evaluations of copayments, Rasell considers
the costs and benefits.

Cost sharing is becoming even more trendy. In RAND days, HMOs
typically had little or no cost- sharing. That was one of their attractions.
They relied on their management of care and presumed benefits from prevention
to keep utilization down. Today, some are using copayments as well.

Copayments -- good or bad? Did the RAND study settle this issue?

Rasell's article seems sloppily written, or sloppily edited. For
example, the two "approaches" to cost control in the first part of the
paper (a. copayments and b. different premiums for insurance
policies with different copayments) are two sides of the same coin.
Copayments make insurance less costly to provide because (1) there are
fewer claims and (2) the company doesn't have to pay 100% of the cost of
claims that do come in. If the employee pays at least part of the
insurance premium, the employee has an incentive to choose the policy with
greater copayments. Otherwise, if the employer pays the full premium
either way, no employee will choose a plan with copayments unless it has
some other compensating advantage.

On page 1165 she says that Manning says that "cost-sharing does not
affect the intensity of care, defined as the number and type of services
provided per year" [my emphasis]. This is a mistake.
Manning (p. 258) actually said that cost-sharing does not affect the number
and type of services provided per encounter. In other words, cost
sharing affects how likely you are to see a doctor or be admitted to the
hospital, but not how much you spend once you are there. Manning's
actual idea fits better with the point Rasell is trying to make, so this
looks like an editing error.

International comparison of contact rates. US has fewer physician
visits per year than other advanced countries. Hospital bed days
same as UK, less than other countries. Outpatient surgery somewhat
compensates for this, she says, but has no figures.

Even though cost sharing is the norm in the US, our health care spending
is growing faster than other countries'. Evidently the other countries'
methods of controlling their health spending are more effective than ours
yet don't discourage demand as much.

Cost sharing and unnecessary care.
Different Siu article cited to show utilization of both appropriate
and inappropriate care affected, but findings are well summarized here.
Part of what happened was that initial Brook article made big splash,
while the follow-up studies that showed more effect of copayments, particularly on the poor, didn't.

Rasell's reading of follow-up studies shows serious symptoms were more prevalent
for the sick poor on cost-sharing than with free care. The sick poor with free care improved to
where their symptoms were no more prevalent than the sick among the higher income participants.
Children in low income families got less care under cost-sharing than under free care. In better-off families, cost-haring didn't matter.

Cost sharing and health
Among low-income and unhealthy, a statistically significant increase
in serious symptoms, as we saw. Rasell says income-related cost-sharing
has administrative cost.

Whose behavior needs to change to control health care costs? Rasell
says don't blame consumers. She turns to physicians. Cites
example in which physicians raised fees and increased intensity of services
in apparent response to reduction in demand for contacts that followed
start of copayments in a union insurance plan.

Financial incentives to purchase less expensive health insurance raise
concern that allowing plans to compete on price/comprehensiveness will
open doors to risk selection by insurers. Risk-adjusted premium methodology
not well developed.
Insurance comprehensiveness of would be stratified by income.
Already evidence of that.

http://hadm.sph.sc.edu/Courses/Econ/Class4.html
9/24/2003
The views and opinions expressed in this page are strictly those of
the page author. The contents of this page have not been reviewed or approved
by the University of South Carolina.
E-mail: sam.baker@sc.edu